The wavelet transform has been employed as an efficient method in image denoising via wavelet thresholding and shrinkage. The ridgelet transform was recently introduced as an alternative to the wavelet representation of two dimensional signals and image data. In this paper, a BayesShrink ridgelet denoising technique is proposed and its denoising performance is compared with a previous VisuShrink ridgelet method. To derive the results, different wavelet bases such as Daubechies, symlets and biorthogonal are used. Experimental results show that BayesShrink ridgelet denoising yields superior image quality and higher SNR than VisuShrink.